class_docstr: The Object contextual representation head.
  
  Args:
      num_classes(int): The unique number of target classes.
      in_channels(tuple): The number of input channels.
      ocr_mid_channels(int, optional): The number of middle channels in OCRHead. Default: 512.
      ocr_key_channels(int, optional): The number of key channels in ObjectAttentionBlock. Default: 256.
code: def forward(self, feat_list):
      feat_shallow, feat_deep = (
          feat_list[self.indices[0]],
          feat_list[self.indices[1]],
      )
  
      soft_regions = self.aux_head(feat_shallow)
      pixels = self.conv3x3_ocr(feat_deep)
  
      object_regions = self.spatial_gather(pixels, soft_regions)
      ocr = self.spatial_ocr(pixels, object_regions)
  
      logit = self.cls_head(ocr)
      if self.ms_attention:
          return [logit, soft_regions, ocr]
      return [logit, soft_regions]
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.models import layers
label_desc: Use image node_id 2 for calling the OCRHead obj's underlying member method code with example usage: obj.forward(feat_list) and returns: list, list